The present disclosure relates to complex discrete manufacturing environments, and in particular to the determination and representation of resource loading profiles.
Resource loading analysis for complex discrete manufacturing is the process of determining future resource requirements in view of the scheduled production tasks for a current order mix. Complex discrete manufacturing refers to manufacturing to produce a relatively large number of orders of different kinds, where a significant number of orders require a considerable number of production tasks. “Resources” may include machine tools or other equipment required to perform production tasks, as well as operators of such equipment. For a given set of orders to be produced, resource loading analysis may produce an estimate of the amount of work required over a period of time from each resource and group of resources in the factory.
Complex discrete manufacturing environments are rather unpredictable because of uncertainty and variability in production processes. Conventional resource loading analysis deals with uncertainty and variability by segmenting the time period of interest into “time buckets” and estimating the average load for each bucket. The preferable duration of the time buckets depends on the degree of variability. The greater the variability, the longer the necessary duration of the time buckets in order to produce reliable results. However by using time buckets for resource loading analysis, peaks in loads on resources may be concealed, thereby possibly failing to indicate resource overloads. Thus, the only way to prevent overloads when time-bucket-based resource loading analysis is performed is to create excess and/or flexible capacity. But excess capacity may reduce efficiency, and it is often impossible to provide flexible resource capacity.